In this paper we introduce the Smooth Permanent Surge [SPS] model. The model is an integrated non lineal moving average process with possibly unit roots in the moving average coefficients. The process nests the Stochastic Permanent Break [STOPBREAK] process by Engle and Smith (1999) and in a...

In this paper, we propose two parametric alternatives to the standard GARCH model. They allow the conditional variance to have a smooth time-varying structure of either additive or multiplicative type. The suggested parameterizations describe both nonlinearity and structural change in the...

In this paper we introduce several test statistics of testing the null hypotheses of a random walk (with or without drift) against models that accommodate a smooth nonlinear shift in the level, the dynamic structure, and the trend. We derive analytical limiting distributions for all tests....

In this paper we derive tests for parameter constancy when the data generating process is non-stationary against the hypothesis that the parameters of the model change smoothly over time. To obtain the asymptotic distributions of the tests we generalize many theoretical results, as well as new...

This paper is concerned with efficient GMM estimation and inference in GARCH models. Sufficient conditions for the estimator to be consistent and asymptotically normal are established for the GARCH(1,1) conditional variance process. In addition efficiency results are obtained in the general...

In this paper we show the consequences of applying a panel unit root test when testing for a purchasing power parity relationship. The distribution of the tests investigated, including the IPS test of Im et al (1997), are influenced by a common stochastic trend which is usually not accounted...

The panel cointegration test of Larsson et al (1998) test for the maximum number of cointegrating relations in a dynamic panel given the assumption of a common cointegrating rank. This paper presents a test for this assumption. The test is based on the test statistic of Larsson et al (1998) and...

The LM type linearity test for STAR nonlinearities is severely distorted when the process is governed by conditional heteroskedasticity. In order to correct the test we propose a parametric bootstrap. It is shown, by means of Monte Carlo methods, that the bootstrap test is almost exact.

In this paper, new noncausality tests relying on a general nonlinear framework are proposed and their performance studied by a Monte Carlo experiment and a variety of nonlinear artificial series. Two of the tests are based on a Taylor expansion of the nonlinear model around a given point in the...

This paper presents a general likelihood-based framework for inference in panel-VAR models with cointegrating restrictions. The cointegrating relations are restricted to each cross-section while the rest of the model is unrestricted. The homogenous restriction of common cointegrating space is...